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COCO8-multitask dataset for the Multitask Model #532
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👋 Hello @stedavkle, thank you for submitting a YOLO 🚀 PR! To allow your work to be integrated as seamlessly as possible, we advise you to:
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@stedavkle hello! Thank you for your contribution to the YOLO community with your multitask dataset! It's great to see innovations like yours that extend the capabilities of models to handle multiple tasks simultaneously. 🌟 For those interested in the multitask model and dataset, please refer to the original issue and documentation provided by the contributor in the Ultralytics repository. If you have any specific questions or need support regarding the Ultralytics HUB, feel free to consult our documentation at https://docs.ultralytics.com/hub or reach out here with your queries. Keep up the fantastic work, and thank you for being a part of the YOLO and Ultralytics community! 🚀 |
👋 Hello there! We wanted to let you know that we've decided to close this pull request due to inactivity. We appreciate the effort you put into contributing to our project, but unfortunately, not all contributions are suitable or aligned with our product roadmap. We hope you understand our decision, and please don't let it discourage you from contributing to open source projects in the future. We value all of our community members and their contributions, and we encourage you to keep exploring new projects and ways to get involved. For additional resources and information, please see the links below:
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I added a dataset in a new YOLO multitask format. This is an evaluation dataset for the model developed by me that combines the segmentation and keypoint detection tasks in one head.
See #6949 on the ultralytics repo.
Documentation
I have read the CLA Document and I hereby sign the CLA
🛠️ PR Summary
Made with ❤️ by Ultralytics Actions
📊 Key Changes
COCO8-multitask
, was added. This dataset is a subset of the larger COCO dataset, containing 8 images.🎯 Purpose & Impact
🌟 Summary
The new
COCO8-multitask
dataset has been introduced to aid in quick testing and experimentation, featuring a carefully selected set of images and annotations for multitask learning.